Algorithms for quantifying associations, independence testing and causal inference from data.

(Conditional) Independence testing & Markov blanket feature selection using k-NN mutual information and conditional mutual information estimators. Supports continuous, discrete, and mixed data, as well as multiprocessing.

Python package for (conditional) independence testing and statistical functions related to causality.

analysis of contingency tables and their residuals, with a bootstrap correction for multiple testing